Most large-scale datasets contain noisy labels. The techniques to alleviate the effect of noisy labels can be divided into two categories: (1) detecting noisy labels and then cleansing potential noisy labels or reduce their impacts [1]} [2]} [3]}; (2) directly training noise-robust models with noisy labels [4]} [5]} [6]}.
